code: def TensorListReserve(context, node):
      element_shape = context[node.inputs[0]]
      num_elements = context[node.inputs[1]]
      element_dtype = node.attr.get("element_dtype")
      dtype = builtin_to_string(element_dtype)
  
      if element_shape is not None and all(
          _np.atleast_1d(element_shape.val) != -1
      ):
          ls = mb.make_list(
              init_length=num_elements,
              elem_shape=tuple(element_shape.val.tolist()),
              dynamic_length=num_elements.val is None,
              dtype=dtype,
              name=node.name,
          )
      else:
          ls = mb.tf_make_list(
              init_length=num_elements,
              dtype=dtype,
              dynamic_length=num_elements.val is None,
              name=node.name,
          )
      context.add(node.name, ls)
  
file_path: coremltools/coremltools/converters/mil/frontend/tensorflow2/ops.py
imports: import numpy
  from coremltools.converters.mil.frontend.tensorflow.convert_utils import convert_graph
  from coremltools.converters.mil.frontend.tensorflow.ops import _transpose_NCDHW_to_NDHWC, _transpose_NCHW_to_NHWC, _transpose_NDHWC_to_NCDHW, _transpose_NHWC_to_NCHW
  from coremltools.converters.mil.frontend.tensorflow.tf_op_registry import register_tf_op
  from coremltools.converters.mil.mil import Builder
  from coremltools.converters.mil.mil.types import builtin_to_string
  from coremltools.converters.mil.mil.types.symbolic import any_symbolic
label_desc: Use image node_id 8 for calling a global function with example usage: TensorListReserve(context, node) without return types